CN111651846A - Automatic optimization method for pipeline design of refrigeration equipment - Google Patents
Automatic optimization method for pipeline design of refrigeration equipment Download PDFInfo
- Publication number
- CN111651846A CN111651846A CN202010489909.3A CN202010489909A CN111651846A CN 111651846 A CN111651846 A CN 111651846A CN 202010489909 A CN202010489909 A CN 202010489909A CN 111651846 A CN111651846 A CN 111651846A
- Authority
- CN
- China
- Prior art keywords
- pipeline
- design
- parameters
- optimization
- refrigeration equipment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/14—Pipes
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a refrigeration equipment pipeline design technology, and discloses an automatic optimization method for refrigeration equipment pipeline design, which realizes automatic optimization of vibration, noise and cost of pipeline design and solves the problem of use limitation of the traditional optimization scheme. The method comprises the steps of carrying out parametric design on a pipeline system, integrating the pipeline system into a pipeline design specification, carrying out sensitivity analysis on parameters, extracting key design parameters, defining a key parameter change space, establishing a simulation optimization target based on optimization simulation software, carrying out automatic parameter optimization by adopting a multi-target genetic algorithm, a multi-target self-adaptive algorithm and the like, and returning an optimal solution to a parameter model for iteration until an optimal pipeline structure meeting the process specification is obtained.
Description
Technical Field
The invention relates to a refrigeration equipment pipeline design technology, in particular to an automatic optimization method for refrigeration equipment pipeline design.
Background
At present, the refrigeration industry almost enters the full frequency conversion era, and the problems of vibration and noise in the development process of frequency conversion products are pain points and difficulties faced by the whole refrigeration industry. In a refrigeration system, a compressor provides circulating power for the system, the compressor is a power source and also a vibration noise source, and a pipeline system connected with the compressor is a main way for transmitting the vibration of the compressor. Therefore, the good and bad design of the pipeline system correspondingly has the functions of inhibiting and amplifying the vibration noise of the compressor, and meanwhile, the self attribute of the pipeline system can also generate vibration and noise.
The frequency conversion compressor has multiple vibration sources with wide working frequency points and wide range, and the refrigeration system has complex pipeline structure and low rigidity, so that the natural frequency of the pipeline system is low and high, and in the working process of the frequency conversion compressor, the frequency of an excitation source is easy to be close to or coincide with the natural frequency of the pipeline system, so that the problems of vibration and noise of the pipeline system are caused, the comfort and reliability of a product are influenced, and especially when the pipeline system has large resonance, the pipeline is directly fatigue-cracked, and serious consequences are caused.
For the problems of vibration and noise of compressor pipelines, the common practice of the industry is to redesign or optimize and modify the pipeline system, and at present, the industry finds a relatively good scheme based on tests or simple simulation in a continuous trial and error mode. Such as: the designer designs the pipeline according to experience at first, then carries out pipeline vibration noise verification through finite element simulation or experiment, if the test is unqualified, modifies the pipeline scheme again and verifies repeatedly until a satisfactory result is designed, and because of lacking specific guidance direction, the pipeline design modification period is long, the experiment cost and the pipeline design cost are high, and the effect is poor.
At present, a small number of patents exist in the aspect of air conditioner pipeline optimization, but most of the patents are the unilateral optimization of pipeline vibration, noise and pipeline design cost are not considered, and an automatic optimization method based on a pipeline system design rule is not realized, such as:
the pipeline vibration reduction optimization method with the publication number of CN104408216A discloses a simple and manual optimization method through modal simulation and statics simulation, which is lack of automation and intellectualization and difficult to be applied to a variable frequency pipeline system.
The simulation optimization method of the pipe vibration of the fixed-frequency air conditioner compressor with the publication number of CN109002619A discloses a manual pipeline optimization method taking a single natural frequency as an optimization target.
The multi-objective optimization method for vibration reduction of the air conditioner pipeline structure, the computer readable storage medium and the terminal with the publication number of CN110765569A disclose that the pipeline parameters are used as design parameters to be input into simulation modeling and optimized and analyzed to obtain the pipeline system meeting the vibration standard, but the method has limitations because only a single vibration target is considered and the pipeline design rule is not integrated in the optimization process.
Therefore, the pipeline optimization method in the traditional technology has certain limitations, and is difficult to ensure and solve the problems of vibration, noise, cost and the like of the pipeline design of the refrigeration system in practical application, and is not beneficial to practical application.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the automatic optimization method for the pipeline design of the refrigeration equipment is provided, the automatic optimization of the vibration, noise and cost of the pipeline design is realized, and the problem of use limitation of the traditional optimization scheme is solved.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a method for automatically optimizing the pipeline design of a refrigerating device comprises the following steps:
a. establishing a parameterized three-dimensional model of a refrigeration equipment pipeline, and extracting pipeline design parameters;
b. importing the pipeline parameterized three-dimensional model into simulation software, establishing a finite element simulation model, carrying out vibration and noise simulation, and establishing a vibration, noise and cost optimization target from a simulation result;
c. taking the pipeline design parameters as independent variables, taking the established vibration, noise and cost as optimization targets, designating the change space of the pipeline design parameters, analyzing the sensitivity of the simulation result of the pipeline design parameters, and screening out key design parameters;
d. according to the obtained key design parameters, performing automatic parameter optimization by adopting an optimization algorithm to obtain optimal parameters, feeding the optimal parameters back to the pipeline parameterized three-dimensional model for model updating, and returning to the step a;
e. and (d) repeating the steps a-d until an iteration stopping condition is reached, and obtaining an optimal refrigeration equipment pipeline parameterization three-dimensional model.
As a further optimization, in the step a, a parameterized three-dimensional model of the pipeline of the refrigeration equipment is established and the design parameters of the pipeline are extracted through a parameterized pipeline design system which is integrated with the design specifications of the pipeline; the pipeline parameterized design system is customized and developed based on three-dimensional design software.
As a further optimization, the extracted pipeline design parameters include: the direction, height and radius parameters of each section of pipeline, the spatial position parameters of the four-way valve and the constraint parameters of the pipe orifice at a special position.
As a further optimization, the special position nozzle comprises: the air conditioner comprises a suction and exhaust pipe orifice connected with a compressor, a pipe orifice connected with a four-way valve and a pipe orifice connected with a condenser.
In the step b, during the simulation of vibration and noise, the overall quality of the pipeline is used as a cost target, the stress of the pipeline is used as a vibration simulation target, and the sound pressure level decibel value is used as a noise simulation target.
As a further optimization, in step d, the optimization algorithm includes: MOGA multi-target genetic algorithm, multi-target self-adaptive algorithm, response surface optimization algorithm and the like.
As a further optimization, when a parameterized three-dimensional model of the refrigeration equipment pipeline is established or the model is updated, the design parameters which do not meet the rules are automatically corrected by utilizing the pipeline design specifications.
The invention has the beneficial effects that:
by simulating the pipeline design parameters, multi-objective optimization including vibration, noise, cost and the like is established, and the optimal design scheme is automatically searched in the pipeline design space, so that the optimal design scheme can simultaneously meet the vibration and noise indexes, and the pipeline design cost is lowest.
In addition, because the pipeline system has a complex structure and numerous design parameters, and the pipeline structure after automatic optimization is difficult to ensure the pipeline design specification requirements, the invention provides an automatic judgment and correction method for integrating the pipeline design specification in the automatic optimization process, so that the pipeline with the automatically optimized parameters can meet the actual use requirements.
Drawings
Fig. 1 is a flow chart of an automatic optimization method for a refrigeration equipment pipeline design in an embodiment of the invention.
Detailed Description
The invention aims to provide an automatic optimization method for the pipeline design of refrigeration equipment, which realizes the automatic optimization of the vibration, noise and cost of the pipeline design and solves the problem of use limitation of the traditional optimization scheme. The core idea is as follows: the method comprises the steps of carrying out parametric design on a pipeline system, integrating into a pipeline design specification, carrying out sensitivity analysis on parameters, extracting key design parameters, defining a key parameter change space, establishing a simulation optimization target based on optimization simulation software, carrying out automatic parameter optimization by adopting a multi-target genetic algorithm, a multi-target self-adaptive algorithm and the like, and returning an optimal solution to a parameter model for iteration until an optimal pipeline structure meeting the process specification is obtained.
Example (b):
before pipeline design is performed, professional customized development is performed on the basis of three-dimensional design software (such as Creo, pro, UG and other three-dimensional software) to form a pipeline parameterized design system. The system can realize the functions of extracting pipeline design parameters, managing and the like, and simultaneously the system integrates pipeline design specifications, the pipeline design specifications mainly comprise pipeline processing technology specifications (meeting the pipeline bending processing requirement), the pipeline assembly specifications (meeting the pipeline, a compressor and the assembly requirement of a four-way valve), the pipeline design specifications (meeting the minimum distance between pipes, the pipe and the compressor and the minimum distance between sheet metal parts, the minimum straight-line segment length of the middle section of the pipeline bending, the minimum straight-line segment length of the beginning section and the ending section of the pipeline bending, and the like), and a pipeline structure meeting the pipeline technology specifications is automatically generated when the pipeline is modeled or a model is updated.
As shown in fig. 1, the method for automatically optimizing the design of the refrigeration equipment pipeline in the embodiment includes:
1. establishing a parameterized three-dimensional model of a refrigeration equipment pipeline, and extracting pipeline design parameters;
in the step, a pipeline parameterization design system is used for completing the parameterization modeling of the four-way valve pipeline assembly, pipeline design parameters are extracted, the design parameters mainly comprise three parameters of the position, the height and the radius of each section of pipeline and the spatial position parameters of the four-way valve, and the parameters of the pipe orifices in special positions (a suction and exhaust pipe orifice connected with a compressor, a pipe orifice connected with the four-way valve and a pipe orifice connected with a condenser) are restricted, so that the correct relative position in the updating process is ensured.
2. Importing the pipeline parameterized three-dimensional model into simulation software, establishing a finite element simulation model, carrying out vibration and noise simulation, and establishing a vibration, noise and cost optimization target from a simulation result;
in the step, a pipeline parametric design system is associated with simulation software (such as ansys workbench and the like) to realize bidirectional transmission of parameters, a pipeline three-dimensional model is led into a finite element vibration simulation module (such as a Harmonic Response simulation module of ansys workbench) to carry out pretreatment on the model, set boundary conditions and physical parameters, establish a finite element simulation model, carry out vibration noise simulation, and establish optimization targets of vibration, noise, cost and the like from a simulation result. Specifically, the overall quality of the pipeline is taken as a cost target, the stress of the pipeline is taken as a vibration simulation target, and the sound pressure level decibel value is taken as a noise simulation target. In addition, for different frequency point stresses and different noise decibel values of a pipeline system of the variable frequency compressor, the working frequency range of the compressor is dispersed into N frequency sections, and the maximum value of each section of frequency is taken as a corresponding target.
3. Taking the pipeline design parameters as independent variables, taking the established vibration, noise and cost as optimization targets, designating the change space of the pipeline design parameters, analyzing the sensitivity of the simulation result of the pipeline design parameters, and screening out key design parameters;
in the step, the finally obtained optimal design model can meet various indexes such as vibration, noise and the like through multi-objective optimization, the cost is guaranteed to be the lowest, and the accuracy of design can be improved through screening of design parameters.
4. According to the obtained key design parameters, an optimization algorithm is adopted to automatically optimize the parameters to obtain optimal parameters, the optimal parameters are fed back to the pipeline parameterized three-dimensional model to update the model, and the step 1 is returned;
in the step, according to the key design parameters obtained in the step 3, an optimization algorithm such as an MOGA (multi-object genetic algorithm), a multi-object adaptive algorithm, a response surface optimization algorithm and the like is adopted to automatically optimize the parameters, so that optimal parameters are obtained, and the optimal parameters are returned to the pipeline parameterized three-dimensional model in the pipeline parameterized design system.
5. And (4) repeating the steps 1-4 until an iteration stop condition is reached, and obtaining an optimal refrigeration equipment pipeline parameterization three-dimensional model.
The optimization process is to continuously drive the three-dimensional model to change through design parameters, realize new simulation, continuously iterate calculation and search an optimal scheme in a parameter optimization space. The three-dimensional pipeline model is changed every time, parameters which do not meet the rules are automatically corrected by using the pipeline design rules, so that the pipeline model with optimized parameters meets the requirements of practical application.
The automatic optimization scheme can identify sensitive design parameters, automatically searches an optimal design scheme based on pipeline design specifications in a pipeline design space, meets the vibration noise standard and the process requirement, and is high in design success rate and strong in practicability through test verification.
Claims (7)
1. A method for automatically optimizing the design of a refrigeration equipment pipeline is characterized by comprising the following steps:
a. establishing a parameterized three-dimensional model of a refrigeration equipment pipeline, and extracting pipeline design parameters;
b. importing the pipeline parameterized three-dimensional model into simulation software, establishing a finite element simulation model, carrying out vibration and noise simulation, and establishing a vibration, noise and cost optimization target from a simulation result;
c. taking the pipeline design parameters as independent variables, taking the established vibration, noise and cost as optimization targets, designating the change space of the pipeline design parameters, analyzing the sensitivity of the simulation result of the pipeline design parameters, and screening out key design parameters;
d. according to the obtained key design parameters, performing automatic parameter optimization by adopting an optimization algorithm to obtain optimal parameters, feeding the optimal parameters back to the pipeline parameterized three-dimensional model for model updating, and returning to the step a;
e. and (d) repeating the steps a-d until an iteration stopping condition is reached, and obtaining an optimal refrigeration equipment pipeline parameterization three-dimensional model.
2. The method for automatically optimizing the piping design of a refrigerating apparatus as set forth in claim 1,
in the step a, a parameterized three-dimensional model of a refrigeration equipment pipeline is established and pipeline design parameters are extracted through a parameterized pipeline design system which is integrated with a pipeline design specification; the pipeline parameterized design system is customized and developed based on three-dimensional design software.
3. The method for automatically optimizing the piping design of a refrigerating apparatus as set forth in claim 1,
the extracted pipeline design parameters include: the direction, height and radius parameters of each section of pipeline, the spatial position parameters of the four-way valve and the constraint parameters of the pipe orifice at a special position.
4. A method for automatically optimizing the piping design of a refrigeration equipment according to claim 3,
the special position nozzle includes: the air conditioner comprises a suction and exhaust pipe orifice connected with a compressor, a pipe orifice connected with a four-way valve and a pipe orifice connected with a condenser.
5. The method for automatically optimizing the piping design of a refrigerating apparatus as set forth in claim 1,
and b, in the vibration and noise simulation, the overall quality of the pipeline is taken as a cost target, the stress of the pipeline is taken as a vibration simulation target, and the sound pressure level decibel value is taken as a noise simulation target.
6. The method for automatically optimizing the piping design of a refrigerating apparatus as set forth in claim 1,
in step d, the optimization algorithm comprises: MOGA multi-target genetic algorithm, multi-target self-adaptive algorithm, response surface optimization algorithm and the like.
7. A method for automatically optimizing the piping design of a refrigeration equipment according to any one of claims 2 to 6,
when a parameterized three-dimensional model of the refrigeration equipment pipeline is established or the model is updated, the design parameters which do not meet the rules are automatically corrected by utilizing the pipeline design specifications.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010489909.3A CN111651846B (en) | 2020-06-02 | 2020-06-02 | Automatic optimization method for pipeline design of refrigeration equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010489909.3A CN111651846B (en) | 2020-06-02 | 2020-06-02 | Automatic optimization method for pipeline design of refrigeration equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111651846A true CN111651846A (en) | 2020-09-11 |
| CN111651846B CN111651846B (en) | 2023-02-03 |
Family
ID=72342681
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010489909.3A Active CN111651846B (en) | 2020-06-02 | 2020-06-02 | Automatic optimization method for pipeline design of refrigeration equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111651846B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113255084A (en) * | 2021-07-07 | 2021-08-13 | 盛瑞传动股份有限公司 | Rapid optimization method of gear noise radiation based on response surface method |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU76431U1 (en) * | 2008-04-24 | 2008-09-20 | Адольф Александрович Лычагин | SORPTION HEAT USING REFRIGERATING MACHINE |
| CN201293499Y (en) * | 2008-10-25 | 2009-08-19 | 广东美的电器股份有限公司 | Split type air conditioner throttling device |
| JP2013030186A (en) * | 2012-10-01 | 2013-02-07 | Hitachi Ltd | Noise analysis design method and noise analysis design apparatus |
| CN103034752A (en) * | 2012-11-19 | 2013-04-10 | 上海英波声学工程技术有限公司 | System and method for predicting noise of air conditioner pipe |
| CN104408216A (en) * | 2014-09-04 | 2015-03-11 | 广东西屋康达空调有限公司 | Optimization method of vibration attenuation of pipeline |
| CN106934162A (en) * | 2017-03-15 | 2017-07-07 | 广东工业大学 | A kind of noise of motor optimization method and device based on Magnetic Circuit Method Yu FInite Element |
| CN109063312A (en) * | 2018-07-26 | 2018-12-21 | 四川长虹空调有限公司 | Transducer air conditioning two-spool compressor piping system Vibration Simulation method |
| CN109190189A (en) * | 2018-08-10 | 2019-01-11 | 武汉理工大学 | A kind of body side wall safety component hybrid variable design method for optimization of matching |
| CN109711049A (en) * | 2018-12-26 | 2019-05-03 | 北京工业大学 | A kind of hybrid-type Metro Air conditioner water cooler efficiency estimation method |
| CN109779940A (en) * | 2019-02-26 | 2019-05-21 | 苏州洪昇新能源科技有限公司 | A kind of EBM blower managing and control system |
| CN110287569A (en) * | 2019-06-18 | 2019-09-27 | 珠海格力电器股份有限公司 | The analysis method and device of air-conditioning duct design |
| CN110765569A (en) * | 2019-09-05 | 2020-02-07 | 珠海格力电器股份有限公司 | Multi-objective optimization method for vibration reduction of air conditioner pipeline structure, computer readable storage medium and terminal |
| CN111191316A (en) * | 2020-01-06 | 2020-05-22 | 沈阳建筑大学 | Response surface-based building natural ventilation performance optimization model and optimization method |
-
2020
- 2020-06-02 CN CN202010489909.3A patent/CN111651846B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU76431U1 (en) * | 2008-04-24 | 2008-09-20 | Адольф Александрович Лычагин | SORPTION HEAT USING REFRIGERATING MACHINE |
| CN201293499Y (en) * | 2008-10-25 | 2009-08-19 | 广东美的电器股份有限公司 | Split type air conditioner throttling device |
| JP2013030186A (en) * | 2012-10-01 | 2013-02-07 | Hitachi Ltd | Noise analysis design method and noise analysis design apparatus |
| CN103034752A (en) * | 2012-11-19 | 2013-04-10 | 上海英波声学工程技术有限公司 | System and method for predicting noise of air conditioner pipe |
| CN104408216A (en) * | 2014-09-04 | 2015-03-11 | 广东西屋康达空调有限公司 | Optimization method of vibration attenuation of pipeline |
| CN106934162A (en) * | 2017-03-15 | 2017-07-07 | 广东工业大学 | A kind of noise of motor optimization method and device based on Magnetic Circuit Method Yu FInite Element |
| CN109063312A (en) * | 2018-07-26 | 2018-12-21 | 四川长虹空调有限公司 | Transducer air conditioning two-spool compressor piping system Vibration Simulation method |
| CN109190189A (en) * | 2018-08-10 | 2019-01-11 | 武汉理工大学 | A kind of body side wall safety component hybrid variable design method for optimization of matching |
| CN109711049A (en) * | 2018-12-26 | 2019-05-03 | 北京工业大学 | A kind of hybrid-type Metro Air conditioner water cooler efficiency estimation method |
| CN109779940A (en) * | 2019-02-26 | 2019-05-21 | 苏州洪昇新能源科技有限公司 | A kind of EBM blower managing and control system |
| CN110287569A (en) * | 2019-06-18 | 2019-09-27 | 珠海格力电器股份有限公司 | The analysis method and device of air-conditioning duct design |
| CN110765569A (en) * | 2019-09-05 | 2020-02-07 | 珠海格力电器股份有限公司 | Multi-objective optimization method for vibration reduction of air conditioner pipeline structure, computer readable storage medium and terminal |
| CN111191316A (en) * | 2020-01-06 | 2020-05-22 | 沈阳建筑大学 | Response surface-based building natural ventilation performance optimization model and optimization method |
Non-Patent Citations (9)
| Title |
|---|
| SEONG-RYEOL HAN: "Investigation of vibration damping characteristics of automotive air conditioning pipeline systems", 《INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING》 * |
| 佚名: "空调管路随机振动分析与优化", 《HTTPS://ARTICLES.E-WORKS.NET.CN/CAE/ARTICLE142088.HTM》 * |
| 兰江华: "仿真分析与振动试验在空调管路系统优化中的应用", 《2014年中国家用电器技术大会》 * |
| 吴广平等: "空调器配管系统优化设计", 《家电科技》 * |
| 江陵: "空调压缩机匹配振动性能的数字化仿真", 《 2001年全国空调器、电冰箱(柜)及压缩机学术交流会》 * |
| 王春: "空调压缩机管路系统仿真设计优化与分析研究", 《家电科技》 * |
| 王海东等: "基于多目标遗传算法的三轴振动夹具结构参数优化设计分析", 《航天器环境工程》 * |
| 邵佩佩: "空调管路系统的振动分析及优化设计", 《 2017年中国家用电器技术大会》 * |
| 陈丽娟: "分体式空调系统噪声特性分析与降噪优化设计研究", 《万方》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113255084A (en) * | 2021-07-07 | 2021-08-13 | 盛瑞传动股份有限公司 | Rapid optimization method of gear noise radiation based on response surface method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111651846B (en) | 2023-02-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111881605B (en) | Automatic optimization design method for variable frequency air conditioner compressor pipeline | |
| CN107688710B (en) | Valve parameterization family building method based on Revit platform | |
| CN107273924B (en) | Multi-data fusion power plant fault diagnosis method based on fuzzy clustering analysis | |
| CN110765569A (en) | Multi-objective optimization method for vibration reduction of air conditioner pipeline structure, computer readable storage medium and terminal | |
| CA2972540A1 (en) | Plant builder system with integrated simulation and control system configuration | |
| CN106383955A (en) | Method for data conversion between stress analysis and three-dimensional models in pipeline design | |
| US8838420B2 (en) | Model management for computer aided design systems | |
| CN105893669A (en) | Global simulation performance predication method based on data digging | |
| CN111651846B (en) | Automatic optimization method for pipeline design of refrigeration equipment | |
| WO2017169875A1 (en) | Analysis device, analysis method, and storage medium which stores program | |
| Eremeev et al. | Single and multi-objective optimization of a gearbox considering dynamic performance and assemblability | |
| EP4057095B1 (en) | Analysis apparatus, analysis method and program | |
| CN116227055A (en) | Intelligent design method and system for water chilling unit | |
| CN104850711A (en) | Mechanical and electrical product design standard selecting method | |
| WO2022075220A1 (en) | Design assistance system and design assistance method | |
| Zhang et al. | A Knowledge-Embedded End-to-End Intelligent Reasoning Method for Processing Quality of Shaft Parts | |
| CN112182744B (en) | EGR rate prediction method, device, equipment and medium | |
| CN117634861A (en) | Knowledge base-based industrial software execution flow determination method and device | |
| CN116796659A (en) | Gas-liquid two-phase flow pipeline clamp layout optimization method | |
| CN113806891B (en) | Quick design method of clamp suitable for workpiece change | |
| JP4802789B2 (en) | Design value optimization method and design value optimization system | |
| KR101836153B1 (en) | Apparatus and method for generating plant model | |
| Renu et al. | Computationally Assisted Retrieval and Reuse of 3D Solid Models and Assembly Work Instructions | |
| CN117972948A (en) | Ship pipeline resistance intelligent optimization design system based on CATIA software platform | |
| CN117216996A (en) | Building electromechanical comprehensive optimization method based on BIM model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |